// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
// Copyright (C) 2009-2014 Gael Guennebaud <gael.guennebaud@inria.fr>
//
// This Source Code Form is subject to the terms of the Mozilla
// Public License v. 2.0. If a copy of the MPL was not distributed
// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.

#ifndef EIGEN_TRANSPOSE_H
#define EIGEN_TRANSPOSE_H

namespace Eigen {

namespace internal {
    template <typename MatrixType> struct traits<Transpose<MatrixType>> : public traits<MatrixType>
    {
        typedef typename ref_selector<MatrixType>::type MatrixTypeNested;
        typedef typename remove_reference<MatrixTypeNested>::type MatrixTypeNestedPlain;
        enum
        {
            RowsAtCompileTime = MatrixType::ColsAtCompileTime,
            ColsAtCompileTime = MatrixType::RowsAtCompileTime,
            MaxRowsAtCompileTime = MatrixType::MaxColsAtCompileTime,
            MaxColsAtCompileTime = MatrixType::MaxRowsAtCompileTime,
            FlagsLvalueBit = is_lvalue<MatrixType>::value ? LvalueBit : 0,
            Flags0 = traits<MatrixTypeNestedPlain>::Flags & ~(LvalueBit | NestByRefBit),
            Flags1 = Flags0 | FlagsLvalueBit,
            Flags = Flags1 ^ RowMajorBit,
            InnerStrideAtCompileTime = inner_stride_at_compile_time<MatrixType>::ret,
            OuterStrideAtCompileTime = outer_stride_at_compile_time<MatrixType>::ret
        };
    };
}  // namespace internal

template <typename MatrixType, typename StorageKind> class TransposeImpl;

/** \class Transpose
  * \ingroup Core_Module
  *
  * \brief Expression of the transpose of a matrix
  *
  * \tparam MatrixType the type of the object of which we are taking the transpose
  *
  * This class represents an expression of the transpose of a matrix.
  * It is the return type of MatrixBase::transpose() and MatrixBase::adjoint()
  * and most of the time this is the only way it is used.
  *
  * \sa MatrixBase::transpose(), MatrixBase::adjoint()
  */
template <typename MatrixType> class Transpose : public TransposeImpl<MatrixType, typename internal::traits<MatrixType>::StorageKind>
{
public:
    typedef typename internal::ref_selector<MatrixType>::non_const_type MatrixTypeNested;

    typedef typename TransposeImpl<MatrixType, typename internal::traits<MatrixType>::StorageKind>::Base Base;
    EIGEN_GENERIC_PUBLIC_INTERFACE(Transpose)
    typedef typename internal::remove_all<MatrixType>::type NestedExpression;

    EIGEN_DEVICE_FUNC
    explicit EIGEN_STRONG_INLINE Transpose(MatrixType& matrix) : m_matrix(matrix) {}

    EIGEN_INHERIT_ASSIGNMENT_OPERATORS(Transpose)

    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE EIGEN_CONSTEXPR Index rows() const EIGEN_NOEXCEPT { return m_matrix.cols(); }
    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE EIGEN_CONSTEXPR Index cols() const EIGEN_NOEXCEPT { return m_matrix.rows(); }

    /** \returns the nested expression */
    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename internal::remove_all<MatrixTypeNested>::type& nestedExpression() const { return m_matrix; }

    /** \returns the nested expression */
    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE typename internal::remove_reference<MatrixTypeNested>::type& nestedExpression() { return m_matrix; }

    /** \internal */
    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void resize(Index nrows, Index ncols) { m_matrix.resize(ncols, nrows); }

protected:
    typename internal::ref_selector<MatrixType>::non_const_type m_matrix;
};

namespace internal {

    template <typename MatrixType, bool HasDirectAccess = has_direct_access<MatrixType>::ret> struct TransposeImpl_base
    {
        typedef typename dense_xpr_base<Transpose<MatrixType>>::type type;
    };

    template <typename MatrixType> struct TransposeImpl_base<MatrixType, false>
    {
        typedef typename dense_xpr_base<Transpose<MatrixType>>::type type;
    };

}  // end namespace internal

// Generic API dispatcher
template <typename XprType, typename StorageKind> class TransposeImpl : public internal::generic_xpr_base<Transpose<XprType>>::type
{
public:
    typedef typename internal::generic_xpr_base<Transpose<XprType>>::type Base;
};

template <typename MatrixType> class TransposeImpl<MatrixType, Dense> : public internal::TransposeImpl_base<MatrixType>::type
{
public:
    typedef typename internal::TransposeImpl_base<MatrixType>::type Base;
    using Base::coeffRef;
    EIGEN_DENSE_PUBLIC_INTERFACE(Transpose<MatrixType>)
    EIGEN_INHERIT_ASSIGNMENT_OPERATORS(TransposeImpl)

    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index innerStride() const { return derived().nestedExpression().innerStride(); }
    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index outerStride() const { return derived().nestedExpression().outerStride(); }

    typedef typename internal::conditional<internal::is_lvalue<MatrixType>::value, Scalar, const Scalar>::type ScalarWithConstIfNotLvalue;

    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE ScalarWithConstIfNotLvalue* data() { return derived().nestedExpression().data(); }
    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar* data() const { return derived().nestedExpression().data(); }

    // FIXME: shall we keep the const version of coeffRef?
    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar& coeffRef(Index rowId, Index colId) const { return derived().nestedExpression().coeffRef(colId, rowId); }

    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar& coeffRef(Index index) const { return derived().nestedExpression().coeffRef(index); }

protected:
    EIGEN_DEFAULT_EMPTY_CONSTRUCTOR_AND_DESTRUCTOR(TransposeImpl)
};

/** \returns an expression of the transpose of *this.
  *
  * Example: \include MatrixBase_transpose.cpp
  * Output: \verbinclude MatrixBase_transpose.out
  *
  * \warning If you want to replace a matrix by its own transpose, do \b NOT do this:
  * \code
  * m = m.transpose(); // bug!!! caused by aliasing effect
  * \endcode
  * Instead, use the transposeInPlace() method:
  * \code
  * m.transposeInPlace();
  * \endcode
  * which gives Eigen good opportunities for optimization, or alternatively you can also do:
  * \code
  * m = m.transpose().eval();
  * \endcode
  *
  * \sa transposeInPlace(), adjoint() */
template <typename Derived> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Transpose<Derived> DenseBase<Derived>::transpose() { return TransposeReturnType(derived()); }

/** This is the const version of transpose().
  *
  * Make sure you read the warning for transpose() !
  *
  * \sa transposeInPlace(), adjoint() */
template <typename Derived> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE typename DenseBase<Derived>::ConstTransposeReturnType DenseBase<Derived>::transpose() const
{
    return ConstTransposeReturnType(derived());
}

/** \returns an expression of the adjoint (i.e. conjugate transpose) of *this.
  *
  * Example: \include MatrixBase_adjoint.cpp
  * Output: \verbinclude MatrixBase_adjoint.out
  *
  * \warning If you want to replace a matrix by its own adjoint, do \b NOT do this:
  * \code
  * m = m.adjoint(); // bug!!! caused by aliasing effect
  * \endcode
  * Instead, use the adjointInPlace() method:
  * \code
  * m.adjointInPlace();
  * \endcode
  * which gives Eigen good opportunities for optimization, or alternatively you can also do:
  * \code
  * m = m.adjoint().eval();
  * \endcode
  *
  * \sa adjointInPlace(), transpose(), conjugate(), class Transpose, class internal::scalar_conjugate_op */
template <typename Derived> EIGEN_DEVICE_FUNC inline const typename MatrixBase<Derived>::AdjointReturnType MatrixBase<Derived>::adjoint() const
{
    return AdjointReturnType(this->transpose());
}

/***************************************************************************
* "in place" transpose implementation
***************************************************************************/

namespace internal {

    template <typename MatrixType,
              bool IsSquare = (MatrixType::RowsAtCompileTime == MatrixType::ColsAtCompileTime) && MatrixType::RowsAtCompileTime != Dynamic,
              bool MatchPacketSize = (int(MatrixType::RowsAtCompileTime) == int(internal::packet_traits<typename MatrixType::Scalar>::size)) &&
                                     (internal::evaluator<MatrixType>::Flags & PacketAccessBit)>
    struct inplace_transpose_selector;

    template <typename MatrixType> struct inplace_transpose_selector<MatrixType, true, false>
    {  // square matrix
        static void run(MatrixType& m)
        {
            m.matrix().template triangularView<StrictlyUpper>().swap(m.matrix().transpose().template triangularView<StrictlyUpper>());
        }
    };

    template <typename MatrixType> struct inplace_transpose_selector<MatrixType, true, true>
    {  // PacketSize x PacketSize
        static void run(MatrixType& m)
        {
            typedef typename MatrixType::Scalar Scalar;
            typedef typename internal::packet_traits<typename MatrixType::Scalar>::type Packet;
            const Index PacketSize = internal::packet_traits<Scalar>::size;
            const Index Alignment = internal::evaluator<MatrixType>::Alignment;
            PacketBlock<Packet> A;
            for (Index i = 0; i < PacketSize; ++i) A.packet[i] = m.template packetByOuterInner<Alignment>(i, 0);
            internal::ptranspose(A);
            for (Index i = 0; i < PacketSize; ++i) m.template writePacket<Alignment>(m.rowIndexByOuterInner(i, 0), m.colIndexByOuterInner(i, 0), A.packet[i]);
        }
    };

    template <typename MatrixType, Index Alignment> void BlockedInPlaceTranspose(MatrixType& m)
    {
        typedef typename MatrixType::Scalar Scalar;
        typedef typename internal::packet_traits<typename MatrixType::Scalar>::type Packet;
        const Index PacketSize = internal::packet_traits<Scalar>::size;
        eigen_assert(m.rows() == m.cols());
        int row_start = 0;
        for (; row_start + PacketSize <= m.rows(); row_start += PacketSize)
        {
            for (int col_start = row_start; col_start + PacketSize <= m.cols(); col_start += PacketSize)
            {
                PacketBlock<Packet> A;
                if (row_start == col_start)
                {
                    for (Index i = 0; i < PacketSize; ++i) A.packet[i] = m.template packetByOuterInner<Alignment>(row_start + i, col_start);
                    internal::ptranspose(A);
                    for (Index i = 0; i < PacketSize; ++i)
                        m.template writePacket<Alignment>(
                            m.rowIndexByOuterInner(row_start + i, col_start), m.colIndexByOuterInner(row_start + i, col_start), A.packet[i]);
                }
                else
                {
                    PacketBlock<Packet> B;
                    for (Index i = 0; i < PacketSize; ++i)
                    {
                        A.packet[i] = m.template packetByOuterInner<Alignment>(row_start + i, col_start);
                        B.packet[i] = m.template packetByOuterInner<Alignment>(col_start + i, row_start);
                    }
                    internal::ptranspose(A);
                    internal::ptranspose(B);
                    for (Index i = 0; i < PacketSize; ++i)
                    {
                        m.template writePacket<Alignment>(
                            m.rowIndexByOuterInner(row_start + i, col_start), m.colIndexByOuterInner(row_start + i, col_start), B.packet[i]);
                        m.template writePacket<Alignment>(
                            m.rowIndexByOuterInner(col_start + i, row_start), m.colIndexByOuterInner(col_start + i, row_start), A.packet[i]);
                    }
                }
            }
        }
        for (Index row = row_start; row < m.rows(); ++row) { m.matrix().row(row).head(row).swap(m.matrix().col(row).head(row).transpose()); }
    }

    template <typename MatrixType, bool MatchPacketSize> struct inplace_transpose_selector<MatrixType, false, MatchPacketSize>
    {  // non square or dynamic matrix
        static void run(MatrixType& m)
        {
            typedef typename MatrixType::Scalar Scalar;
            if (m.rows() == m.cols())
            {
                const Index PacketSize = internal::packet_traits<Scalar>::size;
                if (!NumTraits<Scalar>::IsComplex && m.rows() >= PacketSize)
                {
                    if ((m.rows() % PacketSize) == 0)
                        BlockedInPlaceTranspose<MatrixType, internal::evaluator<MatrixType>::Alignment>(m);
                    else
                        BlockedInPlaceTranspose<MatrixType, Unaligned>(m);
                }
                else
                {
                    m.matrix().template triangularView<StrictlyUpper>().swap(m.matrix().transpose().template triangularView<StrictlyUpper>());
                }
            }
            else
            {
                m = m.transpose().eval();
            }
        }
    };

}  // end namespace internal

/** This is the "in place" version of transpose(): it replaces \c *this by its own transpose.
  * Thus, doing
  * \code
  * m.transposeInPlace();
  * \endcode
  * has the same effect on m as doing
  * \code
  * m = m.transpose().eval();
  * \endcode
  * and is faster and also safer because in the latter line of code, forgetting the eval() results
  * in a bug caused by \ref TopicAliasing "aliasing".
  *
  * Notice however that this method is only useful if you want to replace a matrix by its own transpose.
  * If you just need the transpose of a matrix, use transpose().
  *
  * \note if the matrix is not square, then \c *this must be a resizable matrix.
  * This excludes (non-square) fixed-size matrices, block-expressions and maps.
  *
  * \sa transpose(), adjoint(), adjointInPlace() */
template <typename Derived> EIGEN_DEVICE_FUNC inline void DenseBase<Derived>::transposeInPlace()
{
    eigen_assert((rows() == cols() || (RowsAtCompileTime == Dynamic && ColsAtCompileTime == Dynamic)) &&
                 "transposeInPlace() called on a non-square non-resizable matrix");
    internal::inplace_transpose_selector<Derived>::run(derived());
}

/***************************************************************************
* "in place" adjoint implementation
***************************************************************************/

/** This is the "in place" version of adjoint(): it replaces \c *this by its own transpose.
  * Thus, doing
  * \code
  * m.adjointInPlace();
  * \endcode
  * has the same effect on m as doing
  * \code
  * m = m.adjoint().eval();
  * \endcode
  * and is faster and also safer because in the latter line of code, forgetting the eval() results
  * in a bug caused by aliasing.
  *
  * Notice however that this method is only useful if you want to replace a matrix by its own adjoint.
  * If you just need the adjoint of a matrix, use adjoint().
  *
  * \note if the matrix is not square, then \c *this must be a resizable matrix.
  * This excludes (non-square) fixed-size matrices, block-expressions and maps.
  *
  * \sa transpose(), adjoint(), transposeInPlace() */
template <typename Derived> EIGEN_DEVICE_FUNC inline void MatrixBase<Derived>::adjointInPlace() { derived() = adjoint().eval(); }

#ifndef EIGEN_NO_DEBUG

// The following is to detect aliasing problems in most common cases.

namespace internal {

    template <bool DestIsTransposed, typename OtherDerived> struct check_transpose_aliasing_compile_time_selector
    {
        enum
        {
            ret = bool(blas_traits<OtherDerived>::IsTransposed) != DestIsTransposed
        };
    };

    template <bool DestIsTransposed, typename BinOp, typename DerivedA, typename DerivedB>
    struct check_transpose_aliasing_compile_time_selector<DestIsTransposed, CwiseBinaryOp<BinOp, DerivedA, DerivedB>>
    {
        enum
        {
            ret = bool(blas_traits<DerivedA>::IsTransposed) != DestIsTransposed || bool(blas_traits<DerivedB>::IsTransposed) != DestIsTransposed
        };
    };

    template <typename Scalar, bool DestIsTransposed, typename OtherDerived> struct check_transpose_aliasing_run_time_selector
    {
        static bool run(const Scalar* dest, const OtherDerived& src)
        {
            return (bool(blas_traits<OtherDerived>::IsTransposed) != DestIsTransposed) && (dest != 0 && dest == (const Scalar*)extract_data(src));
        }
    };

    template <typename Scalar, bool DestIsTransposed, typename BinOp, typename DerivedA, typename DerivedB>
    struct check_transpose_aliasing_run_time_selector<Scalar, DestIsTransposed, CwiseBinaryOp<BinOp, DerivedA, DerivedB>>
    {
        static bool run(const Scalar* dest, const CwiseBinaryOp<BinOp, DerivedA, DerivedB>& src)
        {
            return ((blas_traits<DerivedA>::IsTransposed != DestIsTransposed) && (dest != 0 && dest == (const Scalar*)extract_data(src.lhs()))) ||
                   ((blas_traits<DerivedB>::IsTransposed != DestIsTransposed) && (dest != 0 && dest == (const Scalar*)extract_data(src.rhs())));
        }
    };

    // the following selector, checkTransposeAliasing_impl, based on MightHaveTransposeAliasing,
    // is because when the condition controlling the assert is known at compile time, ICC emits a warning.
    // This is actually a good warning: in expressions that don't have any transposing, the condition is
    // known at compile time to be false, and using that, we can avoid generating the code of the assert again
    // and again for all these expressions that don't need it.

    template <typename Derived,
              typename OtherDerived,
              bool MightHaveTransposeAliasing = check_transpose_aliasing_compile_time_selector<blas_traits<Derived>::IsTransposed, OtherDerived>::ret>
    struct checkTransposeAliasing_impl
    {
        static void run(const Derived& dst, const OtherDerived& other)
        {
            eigen_assert((!check_transpose_aliasing_run_time_selector<typename Derived::Scalar, blas_traits<Derived>::IsTransposed, OtherDerived>::run(
                             extract_data(dst), other)) &&
                         "aliasing detected during transposition, use transposeInPlace() "
                         "or evaluate the rhs into a temporary using .eval()");
        }
    };

    template <typename Derived, typename OtherDerived> struct checkTransposeAliasing_impl<Derived, OtherDerived, false>
    {
        static void run(const Derived&, const OtherDerived&) {}
    };

    template <typename Dst, typename Src> void check_for_aliasing(const Dst& dst, const Src& src)
    {
        if ((!Dst::IsVectorAtCompileTime) && dst.rows() > 1 && dst.cols() > 1)
            internal::checkTransposeAliasing_impl<Dst, Src>::run(dst, src);
    }

}  // end namespace internal

#endif  // EIGEN_NO_DEBUG

}  // end namespace Eigen

#endif  // EIGEN_TRANSPOSE_H
